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Durham University

Institute for Data Science


Our research is organised along four broad subjects: Language, Images, Numbers, and Culture.

All faculties at Durham are stakeholders in all aspects of our research, thereby breaking up the silos of discipline-specific knowledge and skills, and enabling new perspectives on old problems and the development of new ideas. We have identified four research themes, Language, Images, Numbers, and Culture, that cut across our subject-based specific research within our faculties and departments, thereby breaking up the silos of compartmentalized best practice and knowledge, fostering interdisciplinary dialogue and enabling the development of new and exciting ideas. It is easy to imagine, for example, that researchers working in Digital Humanities will be interested in cross correlating artefact in various museums to enhance the experience of visitors by providing additional context. For this, they would naturally use tools and methods developed in natural language or image processing and they would have to reflect on the cultural implications of their work. Similar logic applies also to research related to Scientific and Environmental Data or Quantitative Social Sciences, and it will also impact on ideas on Business Development and the Economy of the Future.

The context of Data Science

Data of relentlessly increasing volume, velocity, and variety, their acquisition or generation, their processing and collection, their storage, management and curation, their analysis, visualisation and interpretation are ubiquitous in all strands of research to an extent that “Data Science”, interdisciplinary at its core, has established itself as a discipline in its own right. Artificial Intelligence (AI) is a cornerstone in modern methods of analysing, interpreting, and contextualising ever larger and more intricate data and in making decisions based on them.

Research Theme: Language

Application of natural language processing and automated reading allows the analysis of wide ranges of text documents and the establishment of novel connections, with a large range of repercussions. This includes, for example, the establishment of hitherto unknown correlations between historical and modern texts, or the ability to build dictionaries of names, places, and the occurence of words and phrases throughout time and space.

Research Theme: Images

Images, like, e.g. images of artifacts, of faces, geophysical images, satellite images, permeate practically all aspects of life, our relationships to other people, our local or global environment and our place in the Universe. We will be able to cross-fertilize our research by sharing technology, methods and ideas in the analysis of imagery with repercussions across the board.

Research Theme: Numbers

Research in the Natural and Environmental Sciences habitually feeds on ever more detailed, ever more complex, and ever more voluminous data, either from measurements or from simulations. In the past two decades modern techniques such as machine learning have become ubiquitous in the analysis of these data. The combination of high volume, high velocity data acquired through a vast range of different sensors, from laboratory instruments to arrays of environmental monitors with governmental and sociological requirements of transparency, reproducibility and reusability of the data renders the Natural and Environmental Sciences an ideal testbed for practically all aspects of Data Science.

Research Theme: Culture

AI influences how we publish and reference our work, how we organise our libraries, and how we communicate in different settings (within academia, with the general public, with decision makers in politics and economy). It influences the propagation of news and opinions by eroding the boundary between the creator of documents (author or journalist) and the recipients, who adds by commenting and thereby recontextualising. Using AI in the Arts and Music has opened completely new opportunities for the creation of unique work in the collaboration of human and machine, and again the boundaries between creator and consumer of Arts will be blurred. At the same time, and not only since Cambridge Analytica and the use of data harvested from social media in the recent US election, philosophical, moral and legal questions arise on how to harness the power of AI technology in societal contexts. By contributing to answers to these questions we will participate in the necessary discussion about the future of our society.